Pareto optimal front result of MOCOA. by Hang Zhao (143592)

“…Two types of arrhythmia characterized by significant anomalies in the variables of the HH model were simulated, and corresponding synthetic ECG signals were generated. A multi-objective optimization method based on non-dominated sorting was integrated into the crayfish optimization algorithm (MOCOA). …”

Confusion matrix. by Hang Zhao (143592)

“…Two types of arrhythmia characterized by significant anomalies in the variables of the HH model were simulated, and corresponding synthetic ECG signals were generated. A multi-objective optimization method based on non-dominated sorting was integrated into the crayfish optimization algorithm (MOCOA). …”

Action potential of sample points in model 1. by Hang Zhao (143592)

“…Two types of arrhythmia characterized by significant anomalies in the variables of the HH model were simulated, and corresponding synthetic ECG signals were generated. A multi-objective optimization method based on non-dominated sorting was integrated into the crayfish optimization algorithm (MOCOA). …”

Performance validation on the MIT-BIH database. by Hang Zhao (143592)

“…Two types of arrhythmia characterized by significant anomalies in the variables of the HH model were simulated, and corresponding synthetic ECG signals were generated. A multi-objective optimization method based on non-dominated sorting was integrated into the crayfish optimization algorithm (MOCOA). …”

Exponentially attenuated sinusoidal function. by Hang Zhao (143592)

“…Two types of arrhythmia characterized by significant anomalies in the variables of the HH model were simulated, and corresponding synthetic ECG signals were generated. A multi-objective optimization method based on non-dominated sorting was integrated into the crayfish optimization algorithm (MOCOA). …”

Performance comparison with other papers. by Hang Zhao (143592)

“…Two types of arrhythmia characterized by significant anomalies in the variables of the HH model were simulated, and corresponding synthetic ECG signals were generated. A multi-objective optimization method based on non-dominated sorting was integrated into the crayfish optimization algorithm (MOCOA). …”

Action potential of sample points in model 2. by Hang Zhao (143592)

“…Two types of arrhythmia characterized by significant anomalies in the variables of the HH model were simulated, and corresponding synthetic ECG signals were generated. A multi-objective optimization method based on non-dominated sorting was integrated into the crayfish optimization algorithm (MOCOA). …”

Action potential of sample points in model 0. by Hang Zhao (143592)

“…Two types of arrhythmia characterized by significant anomalies in the variables of the HH model were simulated, and corresponding synthetic ECG signals were generated. A multi-objective optimization method based on non-dominated sorting was integrated into the crayfish optimization algorithm (MOCOA). …”

data and code by PENGCHENG LIU (20680641)

“…In the visual studio development environment, open the Fourier trajectory.sln project under the Fourier trajectory directory to open the development package of the Fourier model algorithm for trajectory data.…”

Yellow River Basin Industrial Base Spatio-temporal Monitoring and Impact Assessment Dataset by Libing Wang (21723566)

“…The dataset aggregates data elements and core algorithm codes that underpin the key research stages of the paper, with a focus on demonstrating and reproducing the innovative methodologies employed, rather than directly sharing sensitive raw data or precise measurement values.…”

<b>SAFE: </b><b>s</b><b>ensitive </b><b>a</b><b>nnotation </b><b>f</b><b>inding and </b><b>e</b><b>xtraction from multi-type Chinese maps via hybrid intelligence and knowledge grap... by jiaxin ren (20482655)

“…SAFE not only provides crucial data and technical support for research in geographic information security but also advances the intelligent development of map interpretation.…”

Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles by Soham Savarkar (21811825)

“…<p dir="ltr">This CSV file contains a comprehensively curated dataset comprising physicochemical descriptors and biological assay data for engineered metal oxide nanoparticles. This dataset was specifically developed to support machine learning model training for toxicity prediction and represents the result of an extensive multi-stage data extraction and curation pipeline. …”